Mapping the neural bases of listening effort using high-density diffuse optical tomography (HD-DOT)

Keywords: listening effort, cognitive demand, HD-DOT, naturalistic stimuli

Citation: Bajracharya, A., Sherafati, A., Culver, J. P., & Peelle, J. E. (2022, April). Mapping the neural bases of listening effort using high-density diffuse optical tomography (HD-DOT). In Neural Imaging and Sensing 2022 (p. PC119460G). SPIE.

Conference Presentation Video

Abstract: Effective human spoken communication relies on the quality of speech signals received and the inherent contextual cues. When speech is acoustically degraded, our brains have to adjust the amount of cognitive effort engaged in parsing information. The mechanism behind such compensation might vary depending on the characteristics of the speech stimuli involved. Our research aims to identify the neural bases of effortful listening for speech altered in linguistic complexity and acoustic clarity. Due to practical constraints such as scanner noise, functional Magnetic Resonance Imaging (fMRI) studies attempting to understand spoken language processing often limit stimuli to isolated words devoid of contextual information. These are far from real-world speech scenarios. High-Density Diffuse Optical Tomography (HD-DOT) is a promising wearable technology that enables studying the brain in a non-invasive manner in a naturalistic setting. HD-DOT is well suited to improve our experimental design’s ecological validity by enabling noise-free stimulus presentation while the participants are seated in the scan room. In each session, participants performed tasks such as passive listening to words (~4 min), passive listening to clear and acoustically degraded short stories (~40 min), and a spatial working memory task (~16 min) to localize the MD network. Results based on test-retest sessions conducted on seven young adult participants comparing stimulus complexity and clarity show the recruitment of higher-order brain regions such as the dorsolateral prefrontal cortex and inferior parietal cortex for the more effortful conditions. This recruitment is consistent with the involvement of domain-general processing, such as the multiple demand network.